Dataset Information

Coupling Stable Isotope Labeling and Liquid Chromatography-Trapped Ion Mobility Spectrometry-Time-of-Flight-Tandem Mass Spectrometry for De Novo Mosquito Ovarian Lipid Studies.

ABSTRACT: There is a need to better understand lipid metabolism during mosquito ovarian development. Lipids are the major source of energy supporting ovarian follicles development in mosquitoes. In this paper, we describe the complementary use of stable isotope labeling (SIL) and high-resolution mass spectrometry-based tools for the investigation of de novo triglycerides (TG) and diglycerides (DG) during the ovarian previtellogenic (PVG) stage (4-6 days posteclosion) of female adult Aedes aegypti. Liquid chromatography coupled to high-resolution trapped ion mobility spectrometry-parallel accumulation sequential fragmentation-time-of-flight tandem mass spectrometry (LC-TIMS-PASEF-TOF MS/MS) allowed the separation and quantification of nonlabeled and ²H/¹³C-labeled TG and DG species. Three SIL strategies were evaluated (H₂O/²H₂O with 50:50 and 95:5 mixtures, ¹³C-sucrose, and ¹³C-glucose). Results showed wide applicability with no signs of lipid ovarian impairment by SIL induced toxicity. The analytical workflow based on LC-TIMS-TOF MS/MS provided high confidence and high reproducibility for lipid DG and TG identification and SIL incorporation based on their separation by retention time (RT), collision cross section (CCS), and accurate m/z. In addition, the SIL fatty acid chain incorporation was evaluated using PASEF MS/MS. The ²H/¹³C incorporation into the mosquito diet provided information on how TG lipids are consumed, stored, and recycled during the PVG stage of ovarian development.

SUBMITTER: Tose LV

PROVIDER: S-EPMC9272574 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Ion mobility-mass spectrometry (IM-MS) has become a powerful tool for glycan structural characterization due to its ability to separate isomers and provide collision cross section (CCS) values that facilitate structural assignment. However, IM-based isomer analysis may be complicated by the presence of multiple gas-phase conformations of a single structure that not only increases difficulty in isomer separation but can also introduce the possibility for misinterpretation of conformers as isomers. Here, the ion mobility behavior of several sets of isomeric glycans, analyzed as their permethylated derivatives, in both nonreduced and reduced forms, was investigated by gated-trapped ion mobility spectrometry (G-TIMS). Notably, reducing-end reduction, commonly performed to remove anomerism-induced chromatographic peak splitting, did not eliminate the conformational heterogeneity of permethylated glycans in the gas phase. At a mobility resolving power of ∼100, 14 out of 22 structures showed more than one conformation. These results highlight the need to use IMS devices with high mobility resolving power for better separation of isomers and to acquire additional structural information that can differentiate isomers from conformers. Online electronic excitation dissociation (EED) MS/MS analysis of isomeric glycan mixtures following G-TIMS separation showed that EED can generate isomer-specific fragments while producing nearly identical tandem mass spectra for conformers, thus allowing confident identification of isomers with minimal evidence of any ambiguity resulting from the presence of conformers. G-TIMS EED MS/MS analysis of N-linked glycans released from ovalbumin revealed that several mobility features previously thought to arise from isomeric structures were conformers of a single structure. Finally, analysis of ovalbumin N-glycans from different sources showed that the G-TIMS EED MS/MS approach can accurately determine the batch-to-batch variations in glycosylation profiles at the isomer level, with confident assignment of each isomeric structure.

Project description:Circulating exosomes in bodily fluids such as blood are being actively studied as a rich source of chemical biomarkers for cancer diagnosis and monitoring. Although nucleic acid analysis is a primary tool for the discovery of circulating biomarkers in exosomes, metabolomics holds the potential of expanding the chemical diversity of biomarkers that may be easy and rapid to detect. However, only trace amounts of exosomes can be isolated from a small volume of patient blood, and thus a very sensitive technique is required to analyze the metabolome of exosomes. In this report, we present a workflow that involves multiple cycles of ultracentrifugation for exosome isolation using a starting material of 2 mL of human serum, freeze-thaw-cycles in 50% methanol/water for exosome lysis and metabolite extraction, differential chemical isotope labeling (CIL) of metabolites for enhancing liquid chromatography (LC) separation and improving mass spectrometry (MS) detection, and nanoflow LC-MS (nLC-MS) with captivespray for analysis. As a proof-of-principle, we used dansylation labeling to analyze the amine- and phenol-submetabolomes in two sets of exosome samples isolated from the blood samples of five pancreatic cancer patients before and after chemotherapy treatment. The average number of peak pairs or metabolites detected was 1964 ± 60 per sample for a total of 2446 peak pairs ( n = 10) in the first set and 1948 ± 117 per sample for a total of 2511 peak pairs ( n = 10) in the second set. There were 101 and 94 metabolites positively identified in the first and second set, respectively, and 1580 and 1590 peak pairs with accurate masses matching those of metabolites in the MyCompoundID metabolome database. Analyzing the mixtures of 12C-labeled individual exosome samples spiked with a 13C-labeled pooled sample which served as an internal standard allowed relative quantification of metabolomic changes of exosomes of blood samples collected before and after treatment.

Dataset Information

Coupling Stable Isotope Labeling and Liquid Chromatography-Trapped Ion Mobility Spectrometry-Time-of-Flight-Tandem Mass Spectrometry for De Novo Mosquito Ovarian Lipid Studies.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets